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SummaryA meta‐analysis of thirty‐four restriction tests from nine studies of the natural rate of unemployment hypothesis (NRU) finds the statistical trace of a false empirical hypothesis. A theme of bias and misspecification among those studies that tend to be more supportive of NRU emerges. When combined with a separate meta‐analysis of NRU's falsifying hypothesis, unemployment 'hysteresis' (Stanley 2004a), the natural rate hypothesis may be regarded as empirically 'falsified' (Popper 1959). Monte Carlo simulations validate the meta‐regression methods used here to integrate different restriction tests and to identify their limitations.

1. Introduction -- 2. Identifying and coding meta-analysis data -- 3. Summarizing meta-analysis data -- 4. Publication bias and its discontents -- 5. Explaining economics research -- 6. Economic theory and meta-regression analysis -- 7. Further topics in meta-regression analysis -- 8. Summary and conclusions.

"The purpose of this book is to introduce novice researchers to the tools of meta-analysis and meta-regression analysis and to summarize the state of the art for existing practitioners. Meta-regression analysis addresses the rising 'Tower of Babel' that current economics and business research has become. Meta-analysis is the statistical analysis of previously published, or reported, research findings on a given hypothesis, empirical effect, phenomenon, or policy intervention. It is a systematic review of all the relevant scientific knowledge on a specific subject and is an essential part of the evidence-based practice movement in medicine, education and the social sciences. However, research in economics and business is often fundamentally different from what is found in the sciences and thereby requires different methods for its synthesis--meta-regression analysis. This book develops, summarizes, and applies these meta-analytic methods."--Publisher description

AbstractObjectiveTo estimate the motherhood wage penalty and explain its wide variation across the research literature.BackgroundDetermining the size and understanding the cause of the motherhood wage penalty has important policy implications. If there is no practically significant motherhood wage penalty, then many of the popular explanations for the gender wage gap must be reassessed. If there is a significant motherhood penalty, its cause can help direct policy.MethodWe conduct a systematic review and meta‐regression analysis (MRA) of 49 studies and 1895 estimates of the motherhood wage penalty.ResultsMeta‐regression identifies 23 research characteristics associated with the reported penalty, including: the ways in which that wages are measured, selective reporting, the econometric methods employed, and the omission of relevant worker qualities from the wage equation. After controlling for multiple paths of heterogeneity, selection, misspecification biases, unobserved productivity effects, and selective reporting, our MRA identifies a small, but robust, motherhood wage penalty, mainly driven by a few countries: USA, UK, Germany, and Norway.ConclusionWe estimate that the motherhood wage penalty is about 4% ± 2%, per child, for US mothers. Our findings are most consistent with a perceived productivity effect or with discrimination.

Proceedings of the National Academy of Sciences (PNAS), a peer reviewed journal of the National Academy of Sciences (NAS) - an authoritative source of high-impact, original research that broadly spans the biological, physical, and social sciences.